Research Article |
Corresponding author: Hongmei Xiang ( hmxiang@163.com ) Corresponding author: Wansheng Jiang ( jiangwschina@163.com ) Academic editor: Anthony Herrel
© 2024 Jingfang Li, Mei Xie, Fangpeng Zhang, Juan Shu, Jun Zhang, Zhinuo Zhang, Hongmei Xiang, Wansheng Jiang.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Li J, Xie M, Zhang F, Shu J, Zhang J, Zhang Z, Xiang H, Jiang W (2024) Insights into phylogenetic relationships and gene rearrangements: complete mitogenomes of two sympatric species in the genus Rana (Anura, Ranidae). ZooKeys 1216: 63-82. https://doi.org/10.3897/zookeys.1216.131847
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Mitochondrial genomes (also known as mitogenomes) serve as valuable molecular markers and have found widespread applications in molecular biology and ecology. There is abundant sequence variation in vertebrate mitogenomes, and occasionally, they exhibit gene rearrangements. In this study, two Chinese endemic Rana species, Rana jiemuxiensis and Rana hanluica, were sequenced and analyzed to obtain their complete mitogenomes. The two species were sympatrically distributed in the Zhangjiajie National Forest Park, in Wulingyuan District, Zhangjiajie City, Hunan Province, China. The mitogenome of R. jiemuxiensis was 17,506 bp, while that of R. hanluica was 17,505 bp, each comprising 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), two ribosomal RNA genes (rRNAs), and a non-coding control region (D-loop). The gene content, nucleotide composition, and evolutionary rates of each mitogenome were analyzed and compared with those of congeners. A phylogenetic analysis based on 22 mitogenomes in Rana revealed that the two sympatric species were in two different lineages, indicating that they were genetically separated to a certain extent. Three types of gene rearrangement patterns were identified when examining the gene orders of the 22 Rana mitogenomes. Most of the species shared a second and dominant gene rearrangement pattern that originated from the first ancient pattern. A “tandem duplication – multiple deletion” hypothesis was proposed to explain the evolution of these different gene rearrangement patterns. This study provided valuable data references and enhanced our understanding of the phylogenetic implications and gene rearrangements of Rana species.
China, genome, mitochondrial, phylogeny, Ranine, Zhangjiajie
The amphibian genus Rana Linnaeus, 1758, commonly referred to as the “wood frog” or “brown frog,” represents an early-established group typified by the European wood frog, Rana temporaria Linnaeus, 1758. Over the past two decades, there has been significant taxonomic restructuring within the genus Rana and its ranine counterparts. According to the Amphibian Species of the World online database, the currently reclassified Rana encompasses 52 species distributed throughout temperate Eurasia into Indochina (
Numerous scientific investigations concerning Rana have focused on taxonomy and phylogeny, as well as the discovery of new species and insights into their ecological behaviors. The first discovery of a Rana species in China took place in the Qinling Mountains during the late 19th century, officially named as Rana chensinensis David, 1875 (
Rana hanluica Shen, Jiang & Yang, 2007 and Rana jiemuxiensis Yan, Jiang, Chen, Fang, Jin, Li, Wang, Murphy, Che & Zhang, 2011 are two species belonging to the R. longicrus species group (
The genetic differentiations between the two sympatric species, R. jiemuxiensis and R. hanluica, may play a crucial role in their coexistence, yet this aspect has received limited attention in previous studies. Furthermore, species within the Ranoidae family typically exhibit gene rearrangements in their mitogenomes (
Samples of R. jiemuxiensis and R. hanluica were collected from Zhangjiajie National Forest Park (29°9′39″N, 110°24′58″E), located in the Wulingyuan District of Zhangjiajie City, Hunan Province, China. Permissions for the field survey were obtained for scientific purposes from the local administrations, and the sample collections and experimental protocols were approved by the Biomedical Ethics Committee of Jishou University (Approval No: JSDX–2024–0083). In accordance with the “3R principle” (Reduction, Replacement, and Refinement) as required by the National Ministry of Science and Technology (No. 398 [2006]), only one sample of each species was utilized. Specimens were euthanized humanely and preserved in 85% ethanol as voucher specimens. These specimens were deposited at the Molecular Ecology Laboratory, Zhangjiajie Campus, Jishou University (R. jiemuxiensis, voucher no. JWS20211037; R. hanluica, voucher no. JWS20211131). A small volume of liver tissue was used for molecular experiments. Total DNA was extracted using the DNeasy Blood & Tissue Kit (Qiagen, Hilden, Germany). DNA library construction was performed using the VAHTS Universal DNA Library Prep Kit for Illumina V3 (Vazyme, Nanjing, China). High-throughput sequencing was conducted on the DNBSEQ-T7 platform (Complete Genomics and MGI Tech, Shenzhen, China), generating approximately 30 Gb of raw reads with a read length of 150 bp for each sample.
The complete mitogenomes of R. jiemuxiensis and R. hanluica were assembled using NOVOPlasty 4.3 (
The numbers of observed transitions (s) and transversions (v) for all the PCGs were plotted using DAMBE v7.3.11 (
The complete mitogenome sequences of the available species of the genus Rana were downloaded from NCBI. Twenty-two species in Rana were involved in the final dataset, including R. jiemuxiensis and R. hanluica that we sequenced. This dataset represented the most comprehensive set of mitogenome sequences available to date. An additional species, Odorrana jingdongensis Fei, Ye & Li, 2001, was selected as the outgroup. Each of the 13 PCGs was extracted from the dataset of 23 mitogenomes and checked manually. Subsequently, all PCGs were aligned using the inbuilt MUSCLE module in MEGA and then concatenated to create a combined PCGs dataset. The 13 PCGs concatenated dataset was used to reconstruct the phylogenetic tree using Bayesian inference (BI) (
Gene rearrangement in Rana was analyzed by comparing the gene orders across the entire mitogenomes of the 22 species in Rana, most of which were assembled using NGS techniques (
The complete mitogenomes of R. jiemuxiensis and R. hanluica were circular DNA molecules with lengths of 17,506 bp and 17,505 bp, respectively (Fig.
Characteristics of the mitogenomes of R. jiemuxiensis (RJ) and R. hanluica (RH).
Gene | Position | Length | Strand* | Codons | Anti codon | Intergenic nucleotide# | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
RJ | RH | RJ | RH | RJ | RH | RJ | RH | |||||||
From | To | From | To | Start codons | Stop codons | Start codons | Stop codons | |||||||
tRNALeu (CUN) | 1 | 74 | 1 | 74 | 74 | 74 | H | – | – | – | – | TAG | 0 | 0 |
tRNAThr | 75 | 144 | 75 | 144 | 70 | 70 | H | – | – | – | – | TGT | 0 | 0 |
tRNAPro | 145 | 213 | 145 | 213 | 69 | 69 | L | – | – | – | – | TGG | 1 | 1 |
tRNAPhe | 215 | 286 | 215 | 285 | 72 | 71 | H | – | – | – | – | GAA | 0 | 0 |
12S rRNA | 287 | 1216 | 286 | 1215 | 930 | 930 | H | – | – | – | – | – | 0 | 0 |
tRNAVal | 1217 | 1285 | 1216 | 1284 | 69 | 69 | H | – | – | – | – | TAC | 0 | 0 |
16S rRNA | 1286 | 2860 | 1285 | 2859 | 1575 | 1575 | H | – | – | – | – | – | 0 | 0 |
tRNALeu (UUR) | 2861 | 2934 | 2860 | 2933 | 74 | 74 | H | – | – | – | – | TAA | 47 | 47 |
ND1 | 2982 | 3935 | 2981 | 3934 | 954 | 954 | H | ATT | AGG | ATT | AGG | – | –41 | –41 |
tRNAIle | 3895 | 3965 | 3894 | 3964 | 71 | 71 | H | – | – | – | – | GAT | 1 | 0 |
tRNAGln | 3967 | 4037 | 3965 | 4035 | 71 | 71 | L | – | – | – | – | TAA | –2 | –2 |
tRNAMet | 4036 | 4106 | 4034 | 4104 | 71 | 71 | H | – | – | – | – | CAT | –1 | –1 |
ND2 | 4106 | 5140 | 4104 | 5138 | 1035 | 1035 | H | ATG | TAG | ATG | TAG | – | –2 | –2 |
tRNATrp | 5139 | 5208 | 5137 | 5206 | 70 | 70 | H | – | – | – | – | TCA | –1 | –1 |
tRNAAla | 5208 | 5278 | 5206 | 5276 | 71 | 71 | L | – | – | – | – | TGC | 0 | 0 |
tRNAAsn | 5279 | 5351 | 5277 | 5349 | 73 | 73 | L | – | – | – | – | GTT | 2 | 2 |
NCR | 5354 | 5378 | 5352 | 5377 | 25 | 26 | H | – | – | – | – | – | –2 | –2 |
tRNACys | 5377 | 5442 | 5376 | 5441 | 66 | 66 | L | – | – | – | – | GCA | 0 | 0 |
tRNATyr | 5443 | 5509 | 5442 | 5508 | 67 | 67 | L | – | – | – | – | GTA | 1 | 1 |
COX1 | 5511 | 7064 | 5510 | 7063 | 1554 | 1554 | H | GTG | AGG | GTG | AGG | – | –10 | –10 |
tRNASer (UCN) | 7055 | 7126 | 7054 | 7125 | 72 | 72 | L | – | – | – | – | TGA | 1 | 1 |
tRNAAsp | 7128 | 7196 | 7127 | 7195 | 69 | 69 | H | – | – | – | – | GTC | 135 | 0 |
COX2 | 7332 | 7884 | 7196 | 7883 | 553 | 688 | H | ATG | T(AA) | ATG | T(AA) | – | 0 | 0 |
tRNA (Lys|Asn) | 7885 | 7953 | 7884 | 7952 | 69 | 69 | H | – | – | – | – | TTT | 1 | 1 |
ATP8 | 7955 | 8117 | 7954 | 8115 | 163 | 162 | H | ATG | TAA | ATG | TAA | – | –8 | –7 |
ATP6 | 8110 | 8823 | 8109 | 8791 | 714 | 683 | H | ATG | AGT | ATG | AGT | – | –32 | –1 |
COX3 | 8792 | 9576 | 8791 | 9575 | 785 | 785 | H | ATG | TA(A) | ATG | TA(A) | – | –2 | –2 |
tRNAGly | 9575 | 9644 | 9574 | 9643 | 70 | 70 | H | – | – | – | – | TCC | –46 | –46 |
ND3 | 9599 | 9948 | 9598 | 9947 | 350 | 350 | H | ATG | TA(A) | ATG | TA(A) | – | 35 | 35 |
tRNAArg | 9984 | 10053 | 9983 | 10052 | 70 | 70 | H | – | – | – | – | TCG | 0 | 0 |
ND4L | 10054 | 10338 | 10053 | 10337 | 285 | 285 | H | ATG | TAA | ATG | TAA | – | –7 | –7 |
ND4 | 10332 | 11703 | 10331 | 11702 | 1372 | 1372 | H | ATG | T(AA) | ATG | T(AA) | – | –12 | –12 |
tRNAHis | 11692 | 11759 | 11691 | 11758 | 68 | 68 | H | – | – | – | – | GTG | 0 | 0 |
tRNASer (AGY) | 11760 | 11826 | 11759 | 11825 | 67 | 67 | H | – | – | – | – | GCT | 32 | 31 |
ND5 | 11859 | 13646 | 11857 | 13644 | 1788 | 1788 | H | ATG | AGG | ATG | AGG | – | 624 | 305 |
ND6 | 14271 | 14765 | 13950 | 14444 | 495 | 495 | L | ATG | AGA | ATG | AGA | – | 0 | 0 |
tRNAGlu | 14766 | 14834 | 14445 | 14513 | 69 | 69 | L | – | – | – | – | TTC | 3 | 3 |
CYTB | 14838 | 15980 | 14517 | 15659 | 1143 | 1143 | H | ATG | TAA | ATG | TAA | – | 0 | 0 |
D-Loop | 15981 | 17505 | 15660 | 17505 | 1525 | 1846 | H | – | – | – | – | – | 0 | 0 |
In R. jiemuxiensis and R. hanluica, 13 distinct but overlapping sites were found in their mitogenomes. Three of these overlapping sites were observed between contiguous PCGs, ATP8 and ATP6, ATP6 and COX3, and ND4L and ND4, respectively. Ten gene intervals were also identified, with the largest one located between ND5 and ND6 in both species, measuring 624 bp and 305 bp, respectively. The shortest interval identified was only 1 bp, found in multiple locations within both species. The lengths of the 13 PCGs varied considerably. The longest gene was ND5, which was identical in length in both species at 1788 bp, while the shortest gene was ATP8, with lengths of 162 bp and 163 bp for R. jiemuxiensis and R. hanluica, respectively. Both species had ATG as the start codon for most PCGs, except for ND1 (ATT) and COX1 (GTG). Five typical stop codons, including TAG, AGG, AGA, AGT, and TAA, as well as two kinds of incomplete terminal codons (TA-, T-), were found in the PCGs within their mitogenomes.
The overall base composition of R. jiemuxiensis was as follows: A (24.33%), T (29.11%), G (15.65%), C (30.49%), while that of R. hanluica was A (24.47%), T (29.37%), G (15.65%), C (30.49%). Both species showed an A+T bias with greater A+T than G+C content. Additionally, both species exhibited negative AT skew and GC skew, indicating a predominant bias towards T and C base pairs. The mitogenome sequences of the 22 Rana species compiled in this study ranged from approximately 16,000 bp to 22,000 bp in length, indicating a complex mitogenome evolution among Rana species. However, all species showed a similar A+T content bias and T and C base pair biases that resembled R. jiemuxiensis and R. hanluica (Table
Basal composition (percentage) of the mitogenomes of R. jiemuxiensis and R. hanluica and 20 other Rana species.
Name | T% | C% | A% | G% | Total length | (A+T)% | GC skew | AT skew | Accession number |
---|---|---|---|---|---|---|---|---|---|
R. hanluica | 29.37567 | 30.49626 | 24.47528 | 15.65279 | 17505 | 53.85094 | –0.32164 | –0.091 | PP228844* |
R. jiemuxiensis | 29.11775 | 30.73639 | 24.33298 | 15.81288 | 17506 | 53.45073 | –0.3206 | –0.08952 | PP228843* |
R. dybowskii | 30.53428 | 29.31434 | 24.57703 | 15.57435 | 18864 | 55.11131 | –0.30609 | –0.1081 | KF898355 |
R. chensinensis | 30.69457 | 29.10062 | 24.94212 | 15.26269 | 18808 | 55.63669 | –0.31192 | –0.10339 | KF898356 |
R. draytonii | 29.67805 | 30.06937 | 25.37353 | 14.87905 | 17805 | 55.05158 | –0.33795 | –0.07819 | KP013110 |
R. huanrensis | 30.76512 | 29.04605 | 25.06458 | 15.12425 | 19253 | 55.8297 | –0.31518 | –0.10211 | KT588071 |
R. amurensis | 30.9651 | 29.11325 | 25.5609 | 14.36075 | 18470 | 56.526 | –0.33934 | –0.09561 | KU343216 |
R. chaochiaoensis | 30.19221 | 29.76508 | 24.68411 | 15.3586 | 18591 | 54.87631 | –0.31927 | –0.10037 | KU246048 |
R. kukunoris | 30.70901 | 29.11663 | 25.06005 | 15.11431 | 18863 | 55.76906 | –0.31657 | –0.10129 | KU246049 |
R. omeimontis | 29.75714 | 30.03292 | 24.16155 | 16.04839 | 19934 | 53.91869 | –0.30347 | –0.10378 | KU246050 |
R. temporaria | 30.66239 | 29.20228 | 24.90207 | 15.23326 | 16061 | 55.56446 | –0.31437 | –0.10367 | MH536744 |
R. uenoi | 30.60552 | 29.439 | 24.87979 | 15.07569 | 17370 | 55.48531 | –0.32266 | –0.10319 | MW009067 |
R. johnsi | 29.40915 | 30.72611 | 25.2981 | 14.56665 | 17837 | 54.70724 | –0.35678 | –0.07515 | MZ571365 |
R. dabieshanensis | 29.61744 | 30.22242 | 24.1637 | 15.99644 | 18291 | 53.78114 | –0.3078 | –0.10141 | MW526989 |
R. hanluica | 29.37461 | 30.5133 | 24.4907 | 15.62139 | 19395 | 53.86531 | –0.32279 | –0.09067 | MZ680529 |
R. zhenhaiensis | 29.16111 | 30.59336 | 24.66862 | 15.57691 | 18806 | 53.82973 | –0.32524 | –0.08346 | OL681880 |
R. wuyiensis | 29.43584 | 30.66382 | 25.44937 | 14.45097 | 17779 | 54.88521 | –0.35937 | –0.07263 | OL467321 |
R. catesbeiana | 32.8264 | 26.68979 | 25.99609 | 14.48773 | 17212 | 58.82248 | –0.29633 | –0.11612 | ON746668 |
R. arvalis | 30.69122 | 29.13442 | 24.81986 | 15.35451 | 16143 | 55.51108 | –0.30974 | –0.10577 | MT872666 |
R. coreana | 29.22448 | 30.46958 | 24.7243 | 15.58164 | 22262 | 53.94877 | –0.32329 | –0.08342 | ON920705 |
R. longicrus | 31.33066 | 28.63373 | 25.73209 | 14.30352 | 17833 | 57.06275 | –0.33375 | –0.09811 | MZ680528 |
R. kunyuensis | 31.27726 | 28.63373 | 25.8834 | 14.20561 | 22255 | 57.16066 | –0.3368 | –0.09436 | KF840516 |
Avg. | 30.24552 | 29.62343 | 24.96542 | 15.16564 | 18493 | 55.21094 | –0.3228 | –0.09564 | – |
When examining the average length and nucleotide composition of each PCG (Table
Gene | T% | C% | A% | G% | (A+T)% | Total length | GC skew | AT skew |
---|---|---|---|---|---|---|---|---|
ND1 | 31.8 | 31.5 | 23.7 | 13 | 55.5 | 958 | –0.41964 | –0.14595 |
ND2 | 29 | 32 | 27.7 | 11.3 | 56.7 | 1029 | –0.43921 | –0.02293 |
COX1 | 29.7 | 28 | 24.8 | 17.4 | 54.5 | 1684 | –0.26115 | –0.08991 |
COX2 | 26.3 | 27.5 | 29.7 | 16.5 | 56 | 548 | –0.22897 | 0.060714 |
ATP8 | 28.9 | 28.8 | 32.1 | 10.1 | 61 | 159 | –0.48205 | 0.052459 |
ATP6 | 31.5 | 31.9 | 25.4 | 11.2 | 56.9 | 682 | –0.47541 | –0.10721 |
COX3 | 30.1 | 30.4 | 22.7 | 16.8 | 52.8 | 783 | –0.28358 | –0.14015 |
ND3 | 33.2 | 31.3 | 21 | 14.6 | 54.2 | 337 | –0.38912 | –0.22509 |
ND4L | 30.1 | 31.8 | 24.6 | 13.5 | 54.7 | 282 | –0.38073 | –0.10055 |
ND4 | 30.3 | 31 | 25.9 | 12.9 | 56.2 | 1363 | –0.40278 | –0.07829 |
ND5 | 30.2 | 29.8 | 25.7 | 14.3 | 55.9 | 1779 | –0.3573 | –0.0805 |
ND6 | 34.8 | 10.7 | 17.8 | 36.6 | 52.6 | 491 | 0.02521 | –0.32319 |
CYTB | 29.2 | 32.8 | 24.1 | 13.9 | 53.3 | 1140 | –0.35499 | –0.09568 |
There are a total of 20 amino acids encoded by the PCGs of R. jiemuxiensis and R. hanluica. Among these amino acids, Leu, Ser, and Arg had the highest frequency, while Trp and Met had the lowest. According to the RSCU analysis, Leu, Ser, and Arg were encoded by six codons each; Pro, Thr, Val, Ala, and Gly were encoded by four codons each; Phe, Tyr, Cys, His, Gln, Asn, Lys, Asp, and Glu were encoded by two codons each; Trp and Met were encoded by only one codon each. This reflects a significant bias in codon usage in their mitogenomes (Fig.
Genetic distances were analyzed among 22 Rana species (Fig.
Standard deviations of Ka and Ks for the 13 PCGs across 22 species showed that the data were generally concentrated, with variances of Ks generally greater than those of Ka (Fig.
The tree topologies resulting from BI and ML analyses were identical, with only slight differences in the support values of some nodes (Fig.
As expected, the mitogenomes of Rana species exhibited substantial gene rearrangements and were categorized into three distinct patterns (Fig.
A Phylogenetic gene orders within 22 Rana species and B three patterns of mitochondrial gene rearrangement. Note: The icons represent tRNAs as: (1) L1: tRNALeu (CUN), (2) T: tRNAThr, (3) P: tRNAPro, (4) F: tRNAPhe, (5) V: tRNAVal, (6) L2: tRNALeu (UUR), (7) I: tRNAIle, (8) Q: tRNAGln, (9) M: tRNAMet, (10) W: tRNATrp, (11) A: tRNAAla, (12) N: tRNAAsn, (13) O: NCR, (14) C: tRNACys, (15) Y: tRNATyr, (16) S1: tRNASer (UCN), (17) D: tRNAAsp, (18) K: tRNA(Lys|Asn), (19) G: tRNAGly, (20) R: tRNAArg, (21) H: tRNAHis, (22) S2: tRNASer (AGY), (23) E: tRNAGlu.
We proposed a plausible scenario to explain the mitochondrial gene rearrangements within Rana, considering that duplications and losses are more likely to occur among tRNAs than rRNAs and PCGs. According to the principle of parsimony, a “tandem duplication - multiple deletion” event in a sequence region spanning from ND4 to the D-loop likely triggered the transition from the first ancient pattern to the second pattern. Subsequently, a simple transposition of ND5 would have driven the second pattern to evolve into the third pattern (Fig.
Species verification is crucial for publishing the complete mitogenome of a species. To verify the molecular identification of the species involved in this study, we selected the individual 16S rRNA, ND2, and CYTB genes as target genes because they have abundant resources in NCBI based on previous studies (
Mitochondrial DNAs, or mitogenomes, often serve as valuable molecular markers and have been widely applied in molecular biology and ecological studies. Typically, animal mitogenomes contain 2 rRNAs (12S and 16S rRNA), 22 tRNAs, 13 PCGs, and a control region (also known as the D-loop), with a sequence length usually ranging from 16 to 17 kb (
The utilization of mitochondrial DNA in molecular identification provides a valuable tool in taxonomic studies compared to traditional morphological approaches (
The nucleotide composition of both R. jiemuxiensis and R. hanluica exhibited a distinct A+T rich pattern (Table
The ratio of Ka and Ks is a popular proxy for detecting adaptive evolution, with Ka/Ks > 1 reported in the mitochondrial PCGs of some species (
Mitochondrial DNA sequences, particularly mitogenomes, are increasingly utilized in phylogenetic studies (
The differentiation of species in Rana is possibly associated with geographic isolation and habitat selection. The known distribution altitudes of Rana species were mapped onto the phylogenetic tree (Fig.
Previous studies have revealed that interspecies variations in mitochondrial gene orders are prone to occur in certain groups (
A simple parsimony scenario is proposed to explain the evolutionary process of the three patterns observed in this study (Fig.
The study of gene rearrangement patterns can provide insights into taxonomy and elucidate the complex evolutionary history among species (
The authors have declared that no competing interests exist.
The collection and handling of Rana species in this study were approved by the Biomedical Ethics Committee of Jishou University (Approval No: JSDX–2024–0083).
This work was supported by the Graduate Scientific Research Innovation Project of Hunan Province (CX20231083), National Natural Science Foundation of China (32060128), and Zhilan Foundation (2020040371B/2022010011B).
Conceptualization, H.X. and W.J.; methodology, J.L. and W.J.; software, M.X. and F.Z.; validation, W.J. and J.L.; formal analysis, J.L. and W.J.; investigation, M.X., F.Z. J.S., J.Z. and Z.Z.; resources, J.S., J.Z. and Z.Z.; data curation, J.L.; writing original draft preparation, J.L.; writing review and editing, H.X. and W.J.; visualization, J.L.; supervision, W.J.; project administration, W.J.; funding acquisition, W.J. All authors have read and agreed to the published version of the manuscript.
Hongmei Xiang  https://orcid.org/0009-0006-3251-3726
Wansheng Jiang  https://orcid.org/0000-0002-6498-944X